Analytical Derivation and Comparison of Alarm Similarity Measures

An industrial process includes many devices, variables, and sub-processes that are physically or electronically interconnected. These interconnections imply some level of correlation between different process variables. Since most of the alarms in a process plant are defined on process variables, alarms are also correlated. However, this can be a nuisance to operators, for one fault might trigger a, sometimes large, number of alarms. So, it is essential to find and correct correlated alarms. In this paper, we study different methods and techniques proposed to measure correlation or similarity between alarms. The similarity indices are first analytically calculated and then studied and compared. The results are also validated using Monte-Carlo simulation. Copyright (C) 2021 The Authors.

Automated summary

An industrial process involves interconnected devices, variables, and sub-processes, leading to correlations between different process variables and alarms. Operators may face challenges when dealing with multiple correlated alarms triggered by one fault. Therefore, it is crucial to identify and rectify correlated alarms. Various methods and techniques have been studied to measure the correlation or similarity between alarms, with results validated through Monte-Carlo simulation.